Discovery of InhA inhibitors with anti-mycobacterial activity through a matched molecular pair approach

Identification of antimycobacterial 8-hydroxyquinoline derivatives as in vitro enzymatic inhibitors of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase

The increasing prevalence of drug-resistant Mycobacterium tuberculosis strains stimulates the discovery of new drug candidates. Among them are 8-hydroxyquinoline (8HQ) derivatives that exhibited antimicrobial properties. Unfortunately, there is a lack of data assessing possible targets for this class mainly against Mycobacterium tuberculosis enoyl-acyl carrier protein reductase (MtInhA), a validated target in this field. Thus, the main purpose of this study was to identify 8HQ derivatives that are active against M. tuberculosis and MtInhA. Initially, the screening against the microorganism of a small antimicrobial library and its new derivatives that possess some structural similarity with MtInhA inhibitors identified four 7-substituted-8HQ (series 5 - 5a, 5c, 5d and 5i) and four 5-substituted-8HQ active derivatives (series 7 - 7a, 7c, 7d and 7j). In general, the 7-substituted 8-HQs were more potent and, in the enzymatic assay, were able to inhibit MtInhA at low micromolar range. However, the 5-substituted-8-HQs that presented antimycobacterial activity were not able to inhibit MtInhA. These findings indicate the non-promiscuous nature of 8-HQ derivatives and emphasize the significance of selecting appropriate substituents to achieve in vitro enzyme inhibition. Finally, 7-substituted-8HQ series are promising new derivatives for structure-based drug design and further development.

OptADMET: a web-based tool for substructure modifications to improve ADMET properties of lead compounds

Lead optimization is a crucial step in the drug discovery process, which aims to design potential drug candidates from biologically active hits. During lead optimization, active hits undergo modifications to improve their absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles. Medicinal chemists face key questions regarding which compound(s) should be synthesized next and how to balance multiple ADMET properties. Reliable transformation rules from multiple experimental analyses are critical to improve this decision-making process. We developed OptADMET ( https://cadd.nscc-tj.cn/deploy/optadmet/ ), an integrated web-based platform that provides chemical transformation rules for 32 ADMET properties and leverages prior experimental data for lead optimization. The multiproperty transformation rule database contains a total of 41,779 validated transformation rules generated from the analysis of 177,191 reliable experimental datasets. Additionally, 146,450 rules were generated by analyzing 239,194 molecular data predictions. OptADMET provides the ADMET profiles of all optimized molecules from the queried molecule and enables the prediction of desirable substructure transformations and subsequent validation of drug candidates. OptADMET is based on matched molecular pairs analysis derived from synthetic chemistry, thus providing improved practicality over other methods. OptADMET is designed for use by both experimental and computational scientists.

Terminal Phenoxy Group as a Privileged Moiety of the Drug Scaffold-A Short Review of Most Recent Studies 2013-2022

The terminal phenoxy group is a moiety of many drugs in use today. Numerous literature reports indicated its crucial importance for biological activity; thus, it is a privileged scaffold in medicinal chemistry. This review focuses on the latest achievements in the field of novel potential agents bearing a terminal phenoxy group in 2013-2022. The article provided information on neurological, anticancer, potential lymphoma agent, anti-HIV, antimicrobial, antiparasitic, analgesic, anti-diabetic as well as larvicidal, cholesterol esterase inhibitors, and antithrombotic or agonistic activities towards the adrenergic receptor. Additionally, for selected agents, the Structure-Activity-Relationship (SAR) is also discussed. Thus, this study may help the readers to better understand the nature of the phenoxy group, which will translate into rational drug design and the development of a more efficient drug. To the best of our knowledge, this is the first review devoted to an in-depth analysis of the various activities of compounds bearing terminal phenoxy moiety.

Identification of novel inhibitors for mycobacterial polyketide synthase 13 via in silico drug screening assisted by the parallel compound screening with genetic algorithm-based programs

Identifying small compounds capable of inhibiting Mycobacterium tuberculosis polyketide synthase 13 (Pks13), in charge of final step of mycolic acid biosynthesis, could lead to the development of a novel antituberculosis drug. This study screened for lead compounds capable of targeting M. tuberculosis Pks13 from a chemical library comprising 154,118 compounds through multiple in silico docking simulations. The parallel compound screening (PCS), conducted via two genetic algorithm-based programs was applied in the screening strategy. Out of seven experimentally validated compounds, four compounds showed inhibitory effects on the growth of the model mycobacteria (Mycobacterium smegmatis). Subsequent docking simulation of analogs of the promising leads with the assistance of PCS resulted in the identification of three additional compounds with potent antimycobacterial effects (compounds A1, A2, and A5). Further, molecular dynamics simulation predicted stable interaction between M. tuberculosis Pks13 active site and compound A2, which showed potent antimycobacterial activity comparable to that of isoniazid. The present study demonstrated the efficacy of in silico structure-based drug screening through PCS in antituberculosis drug discovery.

Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion

In the process of drug discovery, the optimization of lead compounds has always been a challenge faced by pharmaceutical chemists. Matched molecular pair analysis (MMPA), a promising tool to efficiently extract and summarize the relationship between structural transformation and property change, is suitable for local structural optimization tasks. Especially, the integration of MMPA with QSAR modeling can further strengthen the utility of MMPA in molecular optimization navigation. In this study, a new semi-automated procedure based on KNIME was developed to support MMPA on both large- and small-scale datasets, including molecular preparation, QSAR model construction, applicability domain evaluation, and MMP calculation and application. Two examples covering regression and classification tasks were provided to gain a better understanding of the importance of MMPA, which has also shown the reliability and utility of this MMPA-by-QSAR pipeline.

Automatic Identification of Analogue Series from Large Compound Data Sets: Methods and Applications

Analogue series play a key role in drug discovery. They arise naturally in lead optimization efforts where analogues are explored based on one or a few core structures. However, it is much harder to accurately identify and extract pairs or series of analogue molecules in large compound databases with no predefined core structures. This methodological review outlines the most common and recent methodological developments to automatically identify analogue series in large libraries. Initial approaches focused on using predefined rules to extract scaffold structures, such as the popular Bemis-Murcko scaffold. Later on, the matched molecular pair concept led to efficient algorithms to identify similar compounds sharing a common core structure by exploring many putative scaffolds for each compound. Further developments of these ideas yielded, on the one hand, approaches for hierarchical scaffold decomposition and, on the other hand, algorithms for the extraction of analogue series based on single-site modifications (so-called matched molecular series) by exploring potential scaffold structures based on systematic molecule fragmentation. Eventually, further development of these approaches resulted in methods for extracting analogue series defined by a single core structure with several substitution sites that allow convenient representations, such as R-group tables. These methods enable the efficient analysis of large data sets with hundreds of thousands or even millions of compounds and have spawned many related methodological developments.

An appraisal of anti-mycobacterial activity with structure-activity relationship of piperazine and its analogues: A review

Piperazine, is privileged six membered nitrogen containing heterocyclic ring also known as 1,4-Diazacyclohexane. Consequently, piperazine is a versatile medicinally important scaffold and is an essential core in numerous marketed drugs with diverse pharmacological activities. In recent years several potent molecules containing piperazine as an essential subunit of the structural frame have been reported, especially against Mycobacterium tuberculosis (MTB). Remarkably, a good number of these reported molecules also displayed potential activity against multidrug-resistant (MDR), and extremely drug-resistant (XDR) strains of MTB. In this review, we have made a concerted effort to retrace anti-mycobacterial compounds for the past five decades (1971-2019) specifically where piperazine has been used as a vital building block. This review will benefit medicinal chemists as it elaborates on the design, rationale and structure-activity relationship (SAR) of the reported potent piperazine based anti-TB molecules, which in turn will assist them in addressing the gaps, exploiting the reported strategies and developing safer, selective, and cost-effective anti-mycobacterial agents.

Improvement of the novel inhibitor for Mycobacterium enoyl-acyl carrier protein reductase (InhA): a structure-activity relationship study of KES4 assisted by in silico structure-based drug screening

InhA or enoyl-acyl carrier protein reductase of Mycobacterium tuberculosis (mtInhA), which controls mycobacterial cell wall construction, has been targeted in the development of antituberculosis drugs. Previously, our in silico structure-based drug screening study identified a novel class of compounds (designated KES4), which is capable of inhibiting the enzymatic activity of mtInhA, as well as mycobacterial growth. The compounds are composed of four ring structures (A-D), and the MD simulation predicted specific interactions with mtInhA of the D-ring and methylene group between the B-ring and C-ring; however, there is still room for improvement in the A-ring structure. In this study, a structure-activity relationship study of the A-ring was attempted with the assistance of in silico docking simulations. In brief, the virtual chemical library of A-ring-modified KES4 was constructed and subjected to in silico docking simulation against mtInhA using the GOLD program. Among the selected candidates, we achieved synthesis of seven compounds, and the bioactivities (effects on InhA activity and mycobacterial growth and cytotoxicity) of the synthesized molecules were evaluated. Among the compounds tested, two candidates (compounds 3d and 3f) exhibited superior properties as mtInhA-targeted anti-infectives for mycobacteria than the lead compound KES4.

Identification of a novel class of small compounds with anti-tuberculosis activity by in silico structure-based drug screening

The enzymes responsible for biotin biosynthesis in mycobacteria have been considered as potential drug targets owing to the important role in infection and cell survival that the biotin synthetic pathway plays in Mycobacterium tuberculosis. Among the enzymes that comprise mycobacterium biotin biosynthesis systems, 7,8-diaminopelargonic acid synthase (DAPAS) plays an essential role during the stationary phase in bacterial growth. In this study, compounds that inhibit mycobacterial DAPAS were screened in the virtual chemical library using an in silico structure-based drug screening (SBDS) technique, and the antimycobacterial activity of the selected compounds was validated experimentally. The DOCK-GOLD programs utilized by in silico SBDS facilitated the identification of a compound, referred to as KMD6, with potent inhibitory effects on the growth of model mycobacteria (M. smegmatis). The subsequent compound search, which was based on the structural features of KMD6, resulted in identification of three additional active compounds, designated as KMDs3, KMDs9 and KMDs10. The inhibitory effect of these compounds was comparable to that of isoniazid, which is a first-line antituberculosis drug. The high antimycobacterial activity of KMD6, KMDs9 and KMDs10 was maintained on the experiment with M. tuberculosis. Of the active compounds identified, KMDs9 would be a promising pharmacophore, owing to its long-term antimycobacterial effect and lack of cytotoxicity.

Discovery of Mycobacterium tuberculosis InhA Inhibitors by Binding Sites Comparison and Ligands Prediction

Drug discovery is usually focused on a single protein target; in this process, existing compounds that bind to related proteins are often ignored. We describe ProBiS plugin, extension of our earlier ProBiS-ligands approach, which for a given protein structure allows prediction of its binding sites and, for each binding site, the ligands from similar binding sites in the Protein Data Bank. We developed a new database of precalculated binding site comparisons of about 290000 proteins to allow fast prediction of binding sites in existing proteins. The plugin enables advanced viewing of predicted binding sites, ligands' poses, and their interactions in three-dimensional graphics. Using the InhA query protein, an enoyl reductase enzyme in the Mycobacterium tuberculosis fatty acid biosynthesis pathway, we predicted its possible ligands and assessed their inhibitory activity experimentally. This resulted in three previously unrecognized inhibitors with novel scaffolds, demonstrating the plugin's utility in the early drug discovery process.

Recent Advances and Structural Features of Enoyl-ACP Reductase Inhibitors of Mycobacterium tuberculosis

Mycobacterium tuberculosis enoyl-ACP reductase (InhA) has been validated as a promising target for antitubercular agents. Isoniazid (INH), the most prescribed drug to treat tuberculosis (TB), inhibits a NADH-dependent InhA that provides precursors of mycolic acids, which are components of the mycobacterial cell wall. It is a pro-drug that needs activation to form the inhibitory INH-NAD adduct by KatG coding for catalase-peroxidase. The INH resistance of M. tuberculosis is caused by mutations in KatG, which may lead to multidrug-resistant TB (MDR-TB). Hence, there is a need for new drugs that can combat MDR-TB. The rationale for the development of new drugs to combat MDR-TB strains is the design of InhA inhibitors that can bypass bioactivation by KatG. In the present review, special attention was paid to discuss the chemical nature and recent developments of direct InhA inhibitors. The InhA inhibitors reported here have significant inhibitory effects against Mtb InhA. The diphenyl ether derivatives have shown slow onset, a tight-binding mechanism, and high affinity at the InhA active site. However, some of the diphenyl ethers have significant in vitro efficacy, which fails to transform into in vivo efficacy. Among the InhA inhibitors, 4-hydroxy-2-pyridones have emerged as a new chemical class with significant InhA inhibitory activity and better pharmacokinetic parameters when compared to diphenyl ethers.